Identifying the network segment responsible for poor audio quality

ABSTRACT

A method, computer system and computer program product for determining a probability that a particular network segment in a telephony network is responsible for poor audio quality associated with a telephone call being transmitted over the telephony network, is provided. A plurality of parameters associated with a telephone call are identified. The plurality of parameters are indicative of audio quality. A probability that a particular network segment is responsible for poor audio quality associated with the telephone call is calculated based on the plurality of parameters. The probability that a particular network segment is responsible for the poor audio quality associated with the telephone call is a function of at least one of the i) duration of the call and ii) call disconnect time relative to call answer time.

TECHNICAL FIELD

The present invention relates generally to monitoring audio qualityexhibited during a telephone call. More specifically, the presentinvention is concerned with identifying a network segment responsiblefor poor audio quality associated with a telephone call.

BACKGROUND

Poor audio quality during a telephone call can be the cause of much userfrustration.

SUMMARY

A method, computer system, and computer program product is provided. Aprocessor of a computing system identifies a plurality of parametersassociated with a telephone call, wherein the plurality of parametersare indicative of audio quality. A probability that a particular networksegment is responsible for poor audio quality associated with thetelephone call is calculated based on the plurality of parameters,wherein the probability that a particular network segment is responsiblefor the poor audio quality associated with the telephone call is afunction of at least one of: i) a duration of the call, and ii) a calldisconnect time relative to a call answer time.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows a simplified, exemplary telephony network, in accordancewith embodiments of the present invention.

FIG. 2 is a block diagram of an analytics system, in accordance withembodiments of the present invention.

FIG. 3 is a flowchart of a method, in accordance with embodiments of thepresent invention.

FIG. 4 is a flowchart of a method, in accordance with embodiments of thepresent invention. FIG. 5 shows a path through a telephony network and asegment of the path most likely to be responsible for poor audioquality, in accordance with embodiments of the present invention.

FIG. 6 shows a path through a telephony network and a segment of thepath most likely to be responsible for poor audio quality, in accordancewith embodiments of the present invention.

FIG. 7 shows a path through a telephony network and a segment of thepath most likely to be responsible for poor audio quality, in accordancewith embodiments of the present invention.

FIG. 8 is a graph illustrating a segment of the path responsible forvoice quality impairment, in accordance with embodiments of the presentinvention.

FIG. 9 is a block diagram of a computing system for implementing methodsof FIGS. 3-4, in accordance with embodiments of the present invention.

DETAILED DESCRIPTION

Often, when the quality of a call's audio is bad, one or both partieswill abandon the call, disconnect, and immediately call the other partyback in an attempt to establish a better connection. Detecting anabandon-and-retry pattern for audio calls is a well-known method ofestablishing a probability that poor audio quality is being experiencedby voice telephony customers. It is know that when a call party isinvoluntarily dropped, the call party may attempt a call back. Anotherway of identifying that audio quality is likely to be a problem is bydetecting an unusual number of short calls. Another example ismonitoring customer complaints.

Additionally, it is known that some country telecoms regulators andconsumer groups place sample telephone calls with a view to identifyingpoor voice quality, particularly where the access is wireless. Theconclusions reached as to what is responsible for the poor audio qualitymay however be flawed.

WO2007005030 describes systems and methods for using distributed networkelements to implement monitoring and data collection concerning selectednetwork parameters. This patent therefore discloses the collection ofdata from a highly instrumented network.

Whilst instrumentation in a telephony network is often used to assistwith attributing the voice quality problems to different parts of thenetwork, it is not always useful. For example, Communication ServiceProviders (CSPs) do not necessarily share internal instrumentation withtelecoms regulators, or, even if the CSPs do share the internalinstrumentation, telecoms regulators would have extreme difficultiesnormalizing such instrumentation across multiple equipment vendors, andmultiple CSPs, in order to perform an accurate and fair evaluation andcomparison.

Receiver reports issued by t Real-Time Transport Control (RTCP) protocolcould, in theory, be used to detect voice over IP (VoIP) audio qualityissues, for example, audio quality issues due to jitter, but in verymany cases such reports are not issued. In other cases, the RTCPprotocol does not apply.

Additionally, core network capacity is generally over-provisionedrelative to access network capacity, because it is generally cheaper toadd resources to the core network rather than to the access network.However, access networks typically have inherent quality challenges(e.g. wireless coverage in the case of wireless access andcapacity-limited backhaul between cell sites and the core network).Consequently, voice quality impairments are generally introduced in theaccess networks. The challenge is to identify which access network iscausing the problem, in particular, whether it is the access networkserving the calling party or the access network serving the calledparty.

It is currently possible for CSPs to analyze voice call charging datarecords and/or call detail records (CDRs) and similar voice callrecords, whether those records are produced by the network or producedoutside of the network, and aggregate that analysis over a large numberof records to establish a probability of there being a problem in aCSP's access network. CDRs have been standardized by the 3rd GenerationPartnership Project (3GPP) and other bodies. However, embodiments of thepresent invention do not require the use of a standardized CDR.

Accordingly, embodiments of the present invention relate to acomputer-implemented method, system and computer program product fordetermining a probability that a particular network segment in atelephony network is responsible for poor audio quality associated witha telephone call being transmitted over the telephony network. Aplurality of parameters associated with a telephone call are identified.The plurality of parameters are indicative of audio quality. Aprobability that a particular network segment is responsible for pooraudio quality associated with the telephone call is calculated based onthe plurality of parameters. The probability that a particular networksegment is responsible for the poor audio quality associated with thetelephone call is a function of at least one of: i) the duration of thecall, and ii) call disconnect time relative to call answer time.

Embodiments of the present invention may apply in case poor audioquality is suspected as being responsible for the disconnect of atelephone call and is used to determine which network segment is likelyto be responsible for the poor audio quality.

FIG. 1 shows a simplified, exemplary telephony network, in accordancewith embodiments of the present invention. The telephony networkcomprises CSP's core network 10 which is connected to CSP2's corenetwork 30 by core transmission network 20. A calling party 60 accessesCSP1's core network 10 via access network 40. Similarly, called party 70accesses CSP2's core network 30 via access network 50. Taking FIG. 1 asan example, a CSP's analysis of CDRs might identify that, in aparticular part of CSP1's access network during a given time period, acertain proportion of the calls illustrate evidence of significant voicequality impairments, but many other calls at the same location do not. Aconclusion may therefore be reached that the cause of the problem ismore likely to exist n the network(s) serving the called parties who areinvolved in such impaired voice calls.

A problem with this approach is that the approach depends so much onestablishing an association between the parties involved in phone callsin CSP1's network. Especially in a wireless network with its varyingcoverage, it is extremely unusual to have more than one such partysharing enough characteristics to make a comparison feasible. One callparty might be close to the cell tower, whilst another call party mightbe at the cell coverage edge. A call party might suffer frominterference whilst another call party might not. One call party mightbe deep in a large building sheltered by trees with wet leaves whilstanother call party might not. So the approach works to an extent, butthe approach needs improvement in terms of attributing the cause of theimpairment.

An improved method is needed to identify the network segment which isresponsible for the poor audio quality and to provide increasedconfidence in any analytics undertaken.

The solution disclosed herein provides, in accordance with embodimentsof the present invention, an improvement over existing methods ofestablishing a probability regarding which access network is responsiblefor introducing voice quality impairments, whilst maintaining theadvantages of being independent of network-specific instrumentation.

In the case of calls dropped or abandoned early in the call, thesolution disclosed can establish, based on a preponderance of evidence,which network segment is responsible for the call drop. Such adetermination could be used, for example, to decide whether or not tocompensate the party charged for the call (seehttp://indianexpress.com/article/technology/tech-news-technology/trai-asks-telecom-operators-to-start-compensating-for-call-drops/).

Embodiments of the present invention may exploit the fact that callanswer is detectable external to the network and is co-incident with:(a) changing voice paths within the network, and (b) certain typicalhuman behavior. Taking (a) and (b) into account means that anidentification can be made as to which network segment is likely to beresponsible for the poor audio quality being exhibited by a particularcall. Such information can then be aggregated across multiple calls,which can then provide for an improved level of confidence in an overallcalculated probability of a general voice quality problem existing at agiven CSP's access network. In other words, a probability can beassociated with each individual network segment to provide an indicationas to how each network segment is performing.

In accordance with embodiments of the present invention, the probabilitythat any given network segment is the source of the voice qualityimpairment is a function of the call duration, the call answer time, andthe call disconnect or abandon/drop time. More specifically, theprobability that a particular network segment is responsible for thepoor audio quality associated with the telephone call is a function ofat least one of: (i) the duration of the call and (ii) the calldisconnect time when a call is disconnected relative to call answer ewhen a call is answered. The term disconnect time as used herein is thetime at which there is first evidence of either party disconnecting. Theterm call duration is the length of the call from when there is firstevidence that the call has been placed to when there is first evidencethat the call has been disconnected. The call duration refers to howlong the call lasts for.

In voice calls, a ring-back tone is invariably inserted at the CSP corenetwork closest to the party being alerted (i.e. the called party).Embodiments of the present invention may exploit the change in call pathfollowing answer, and the typical human pattern where the called partyissues a greeting following answer and the calling party waits to hearthat greeting before saying anything themselves. Calls which areabandoned because of poor audio quality are often abandoned near thebeginning of the call. Consequently, it is possible to infer whichsegments of the network are most likely to be causing an impairment insuch calls by examining the relationship between the time they aredisconnected or abandoned and the call answer time or absence of answer.

FIG. 2 is a block diagram of an analytics system 100 in accordance withembodiments of the present invention. FIG. 3 is a flowchart of a method,in accordance with embodiments of the present invention. FIG. 4 is aflowchart of a method, in accordance with embodiments of the presentinvention. Analytics system 100 comprises call monitoring software 110which includes a call monitor 120. Call monitor 120 monitors a call toidentify at step 200 of FIG. 3 one or more parameters which areindicative of call quality. Exemplary parameters are discussed in moredetail later.

Briefly however, one indicator of poor call quality is where a call isdisconnected early, in such a way as to support a reasonable suspicionthat one of the parties abandoned the call. Most of the time, the reasona party would abandon a call would be because of poor audio quality.Even more indicative of poor audio quality would be if one of theparties placed a new call to the other party a very short time later.

Based on the parameter(s) identified, a determination is made by audioquality identifier 130 at step 210 whether call audio quality is likelyto be a problem. If the answer is no, then the process loops whilstthere are more calls to process.

If poor audio quality is suspected, then in an exemplary embodiment, aCDR is sent to the network segment identifying software 150 by CDRsending component 140 at step 220.

It will be appreciated that the step of monitoring a call to identifyparameters indicative of audio quality may actually comprise analyzing aCDR rather than analyzing/monitoring a call directly. Of course, if thecall is monitored directly, then the necessary parameter information maybe extracted and compiled into a voice call record for forwarding.

Analytics system 100 also comprises, in an exemplary embodiment, thenetwork segment identifying software 110. In an alternative embodiment,however, software 110 and software 150 are remote from one another.

Software 150 comprises a CDR Receiver 160 which receives, at step 300 ofFIG. 4, CDRs or other such call records whether produced by the networkor produced external to the network of calls for which it is likely thatthere is voice quality impairment. CDR Classifier 170 then classifies acall based on the CDR to which the call relates at step 310. The CDRcontains information pertinent to the parameters which have beenidentified as indicative of call quality (e.g. poor audio quality). Asmentioned above, a single call may have multiple CDRs associated withthe call. Therefore, it may be necessary to correlate and analyze morethan one CDR to extract the relevant information. Processing continuesto loop until there are no more CDRs to process.

It will be appreciated however that a CDR record may be sent tocomponent 150 regardless of whether poor call quality is suspected andconsequently steps 200 and 210 of FIG. 3 could be bypassed altogether.

Classification is as follows:

(a) Calls lasting less than p seconds (e.g. p=7) which were disconnectedprior to answer or within q seconds of answer (e.g. q=1). The phrase‘within q seconds’ should not be taken to encompass q itself;

(b) Calls disconnected between q seconds after answer, and r secondsafter answer (e.g. r=8);

(c) Calls disconnected between seconds after answer and s seconds afteranswer (e.g. s=20); and

(d) All other calls (step 350 FIG. 4).

Note, the parameters such as p, q, r and s may be configurable, and canbe tuned based on feedback.

The period between answer and disconnect is the talktime. Wherever atime period is defined as ‘between’ an upper bound and a lower bound,this should be understood to mean including the lower bound butexcluding the upper bound. It should also be appreciated that p, q, rand s are positive real numbers.

In an exemplary embodiment, the following should be true:

s>r>q.

Because r−q must be long enough for the called party to issue agreeting, r−q can be ≥1 second, and because the typical calling partyresponse to that greeting is to identify themselves and perhaps thesubject of the call, one may reasonably conclude that s−r can be ≥3seconds. In an exemplary embodiment, p can be greater than theconfigured time for transfer to voicemail in a call-forward-no-answercondition.

Note that the call that is disconnected within a short period of beingtransferred to voice mail or some other such destination would not be acall that would be considered a suspicious audio quality in the firstplace.

Each network segment (e.g. each access network) has a probabilityassociated with the network segment, wherein a probability indicates thelikelihood that a particular network segment is responsible for the pooraudio quality being exhibited by calls passing through that networksegment.

Probability biasing component 180 is then able to adjust a probabilityassociated with each network segment based on an analysis of each CDRassociated with a call which has been determined to exhibit poor audioquality.

For category (a) calls, the probability is biased to indicate that thecalling party's CSP access network 40 is the access network most likelyto have introduced the voice quality impairment, and that impairments inthe downlink towards the calling user equipment direction 320.

For category (a) calls, there is already some evidence or degree ofprobability of a voice quality impairment on this call based on a knownmethod—e.g. the called party re-attempts the call within a short timeperiod. The value of q is such that the call disconnect being initiatedby the human called party is unlikely, and the value of p is such thatthe call disconnect being a result of the human calling partydisconnecting based on the calling party's belief that the called partyis unlikely to answer, is also unlikely. Thus, an increased probabilitycan be inferred/calculated that the human calling party disconnected thecall due to the human calling party's detection of poor audio qualitywhen the human calling party was listening to the ring-back tone priorto answer. The audio path for this ring-back tone is illustrated in FIG.5. FIG. 5 shows a path through a telephony network and a segment of thepath most likely to be responsible for poor audio quality, in accordancewith embodiments of the present invention. Please note the arrows shownin FIG. 5 are purely used to indicate direction of the audio path,wherein the segment of the path represented by broken lines refers tothe segment of the path that is most likely responsible for the pooraudio quality.

As can be seen, the only access network involved is the access network40 serving the calling party on the downlink, which means that theaccess network is likely to be where the audio quality impairment isbeing introduced.

For category (b) calls, the probability is biased to indicate that thecalled party's CSP access network 50 is the access network most likelyto have introduced the voice quality impairment, and that impairment isin the uplink from the called party's equipment direction 330.

For category (b) calls, there is already some evidence or degree ofprobability of voice quality impairment on this call based on a knownmethod—e.g. one party attempts the call and disconnects within a shorttime period. The typical post-answer human behaviour is that the calledparty issues an audio greeting whilst the calling party remains silentwhilst they listen for that audio greeting following the calling pasty'sperception that the ring-back tone is no longer audible.Consequentially, a call abandoned because of poor voice quality in thatperiod of the call is most likely abandoned because the calling partyperceives that the audio greeting from the called party has beenimpaired en-route. Because the call had not been abandoned prior to thispart of the call, an increased probability may be reasonably inferredthat the segment of the path added upon call answer and transmitting thecalled party's greeting—i.e. the uplink through the called party CSP'saccess network 50 from the called party 70—is where the impairment isoccurring, as shown in FIG. 6. FIG. 6 shows a path through a telephonynetwork and a segment of the path most likely to be responsible for pooraudio quality, in accordance with embodiments of the present invention,wherein the segment of the path represented by broken lines refers tothe segment of the path that is most likely responsible for the pooraudio quality. For category (c) calls, the probability is biased to be afunction of the talktime 340, such that:

(i) calls with a talktime equal to r, are indicated as being most likelyimpaired by the calling party's CSP's access network 40 uplink or thecalled party's CSP's access network 50 downlink (360); and

(ii) for other calls, the indication the calling party's CSP's accessnetwork 40 uplink (callingup) or the called party's CSP's access network50 downlink (calleddown) are the likely sources becomes less as talktimebecomes greater (380).

For category (c) calls, there is already some evidence or degree ofprobability of a voice quality impairment on this call based on a knownmethod—e.g. one party attempts to call the other within a short timeperiod. Because the call has gotten this far, there is a decreasedprobability that the impairment is on the calling party downlink or thecalled party uplink. And thus the impairment is most likely either onthe calling party uplink or the called party downlink. As the calltalktime increases further, this inference becomes gradually lessconfident because some problem could have been introduced in thosenetwork segments previously determined to be probably unimpaired, asshown in FIG. 7. FIG. 7 shows a path through a telephony network and asegment of the path most likely to be responsible for poor audioquality, in accordance with embodiments of the present invention. Pleasenote the arrows shown in FIG. 7 are purely used to indicate direction ofthe audio path, wherein the segment of the path represented by brokenlines refers to the segment of the path that is most likely responsiblefor the poor audio quality.

It should now therefore be appreciated that for most category (c) callsit becomes more difficult to infer where the problem lies as thetalktime increases, which is because the determined probability orlikelihood that the poor audio quality has been introduced by thecalling party's access network uplink or the called party's accessnetwork downlink decreases as talktime increases.

Category (d) calls (i.e. calls greater than or equal to s) are indicatedas having equal probability across all access network segments, as instep 350.

Based on the logic described above, an overview of which networksegment(s) are likely to be responsible for the poor audio qualityexhibited by calls passing through such network segments may beobtained. Equally possible is to get a break down on a call-by-callbasis. Each call can be classified and an identification can be made asto the likely culprit based on that call classification.

FIG. 8 is a graph illustrating a segment of the path responsible forvoice quality impairment, in accordance with embodiments of the presentinvention. FIG. 8 provides a visual illustration of the approachdiscussed supra. They axis of FIG. 8 depicts the probability that acertain network segment is likely to be responsible for poor audioquality. The x axis of FIG. 8 shows the part of the call when disconnectoccurred. For example, if the call was disconnected between placement ofthat call (i.e. seize) a very short period after answer, then there is a90% chance that the calling party's CSP access network is responsibleand that the impairment is in the downlink (i.e. category a) calls). Onthe other hand, if the call was disconnected within a defined shortperiod after that, then there is a 90% chance that the problem is in thecalled party uplink (i.e. category b) calls). The categories of call asdescribed herein are listed against the top of the graph for ease ofcorrelation with the description. The graduations on the x axis are notmeant to represent any particular length of time but are forillustration purposes only.

Referring still to the drawings, FIG. 9 is a block diagram of acomputing system for implementing methods of FIGS. 3-4, in accordancewith embodiments of the present invention. FIG. 9 depicts an exemplarysystem for implementing embodiments of the invention, which includes adata processing 600 suitable for storing and/or executing program codeincluding at least one processor 601 coupled directly or indirectly tomemory elements through a bus system 612. The memory elements mayinclude local memory employed during actual execution of the programcode, bulk storage, and cache memories which provide temporary storageof at least some program code in order to reduce the number of timescode must be retrieved from bulk storage during execution.

The memory elements may include system memory 602 in the form of readonly memory (ROM) 604 and random access memory (RAM) 605. A basicinput/output system (BIOS) 606 may be stored in ROM 604. Software 607may be stored in RAM 605 including system software 608 such as operatingsystem software 609. Software applications 610 may also be stored in RAM605.

The system 600 may also include a primary storage means 611 such as amagnetic hard disk drive and secondary storage means 612 such as amagnetic disc drive and an optical disc drive. The drives and associatedcomputer-readable media provide non-volatile storage ofcomputer-executable instructions, data structures, program modules andother data for the system 600. Software applications may be stored onthe primary and secondary storage means 611, 612 as well as the systemmemory 602.

The computing system 600 may operate in a networked environment usinglogical connections to one or more remote computers via a networkadapter 616.

Input/output devices 613 may be coupled to the system either directly orthrough intervening I/O controllers. A user may enter commands andinformation into the system 600 through input devices such as akeyboard, pointing device, or other input devices (e.g., microphone, joystick, game pad, satellite dish, scanner, or the like). Output devicesmay include speakers, printers, etc. A display device 614 is alsoconnected to system bus 603 via an interface, such as video adapter 615.

The present invention may be a (computer) system, a method, and/or acomputer program product. The computer program product may include acomputer readable storage medium (or media) having computer readableprogram instructions thereon for causing a processor to carry outaspects of the present invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or either source code or object code written in anycombination of one or more programming languages, including an objectoriented programming language such as Smalltalk, C++ or the like, andconventional procedural programming languages, such as the “C”programming language or similar programming languages. The computerreadable program instructions may execute entirely on the user'scomputer, partly on the user's computer, as a stand-alone softwarepackage, partly on the user's computer and partly on a remote computeror entirely on the remote computer or server. In the latter scenario,the remote computer may be connected to the user's computer through anytype of network, including a local area network (LAN) or a wide areanetwork (WAN), or the connection may be made to an external computer(for example, through the Internet using an Internet Service Provider).In some embodiments, electronic circuitry including, for example,programmable logic circuitry, field-programmable gate arrays (FPGA), orprogrammable logic arrays (PLA) may execute the computer readableprogram instructions by utilizing state information of the computerreadable program instructions to personalize the electronic circuitry,in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the block may occur out of theorder noted in the figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

In one embodiment, the system of the present invention may be or includea hardware device such as a computer, portable device, etc. In oneembodiment, the hardware device is or includes a special-purpose device(e.g., computer, machine, portable device) that comprises specialized,non-generic hardware and circuitry (i.e., specialized discretenon-generic analog, digital, and logic based circuitry) for(independently or in combination) particularized for executing onlymethods of the present invention. The specialized discrete non-genericanalog, digital, and logic based circuitry may include proprietaryspecially designed components (e.g., a specialized integrated circuit,such as for example an Application Specific Integrated Circuit (ASIC),designed for only implementing methods of the present invention).

A computer program product of the present invention may include one ormore computer readable hardware storage devices having computer readableprogram code stored therein, said program code containing instructionsexecutable by one or more processors of a computing system (or computersystem) to implement the methods of the present invention.

A computer system of the present invention may include one or moreprocessors, one or more memories, and one or more computer readablehardware storage devices, said one or more hardware storage devicescontaining program code executable by the one or more processors via theone or more memories to implement the methods of the present invention.

The descriptions of the various embodiments of the present inventionhave been presented for purposes of illustration, but are not intendedto be exhaustive or limited to the embodiments disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of the describedembodiments. The terminology used herein was chosen to best explain theprinciples of the embodiments, the practical application or technicalimprovement over technologies found in the marketplace, or to enableothers or ordinary skill in the art to understand the embodimentsdisclosed herein.

What is claimed is:
 1. A method for determining a probability that aparticular network segment in a telephony network is responsible forpoor audio quality associated with a telephone call being transmittedover the telephony network, the method comprising: identifying, by aprocessor of a computing system, a plurality of parameters associatedwith a telephone call, wherein the plurality of parameters areindicative of audio quality; and calculating, by the processor, aprobability that a particular network segment is responsible for pooraudio quality associated with the telephone call based on the pluralityof parameters, wherein the probability that a particular network segmentis responsible for the poor audio quality associated with the telephonecall is a function of at least one of: i) a duration of the call, andii) a call disconnect time relative to a call answer time.
 2. The methodof claim 1, wherein the step of identifying a plurality of parameterscomprises analyzing at least one voice call record associated with thecall.
 3. The method of claim 1, further comprising classifying, by theprocessor, a call according to which network segment is likely to beresponsible for the poor audio quality associated with the telephonecall.
 4. The method of claim 1, further comprising: identifying, by theprocessor, a call lasting less than p seconds which was disconnectedprior to answer or within q seconds of answer; and biasing, by theprocessor, the probability for the identified call to indicate that acalling party's access network downlink is most likely to haveintroduced the poor audio.
 5. The method of claim 1, further comprising:identifying, by the processor, a call disconnected between q secondsafter answer and r seconds after answer where r is greater than q; andbiasing, by the processor, the probability for the identified call toindicate that the called party's access network uplink is most likely tohave introduced the poor audio quality.
 6. The method of claim 1,further comprising: identifying, by the processor, a call disconnectedbetween r seconds after answer and s seconds after answer, wherein theprobability is a function of call talktime.
 7. The method of claim 6,further comprising: biasing, by the processor, the probability for acall having talktime equal to r to indicate that the calling party'saccess network uplink or the called party's access network downlink ismost likely to have introduced the poor audio quality.
 8. The method ofclaim 6, further comprising: biasing, by the processor, the probabilityto indicate that a likelihood that the poor audio quality has beenintroduced by the calling party's access network uplink or the calledparty's access network downlink decreases as talktime increases.
 9. Acomputer system comprising: a processor; a memory device coupled to theprocessor; and a computer readable storage device coupled to theprocessor, wherein the storage device contains program code executableby the processor via the memory device to implement a method fordetermining a probability that a particular network segment in atelephony network is responsible for poor audio quality associated witha telephone call being transmitted over the telephony network, themethod comprising: identifying, by a processor of a computing system, aplurality of parameters associated with a telephone call, wherein theplurality of parameters are indicative of audio quality; andcalculating, by a processor, a probability that a particular networksegment is responsible for poor audio quality associated with thetelephone call based on the plurality of parameters, wherein theprobability that a particular network segment is responsible for thepoor audio quality associated with the telephone call is a function ofat least one of: i) a duration of the call, and ii) a call disconnecttime relative to a call answer time.
 10. The computer system of claim 9,wherein the identifying the plurality of parameters includes analyzingat least one voice call record associated with the call.
 11. Thecomputer system of claim 9, further comprising classifying, by theprocessor, a call according to which network segment is likely to beresponsible for the poor audio quality associated with the telephonecall.
 12. The computer system of claim 9, further comprising:identifying, by the processor, a call lasting less than p seconds whichwas disconnected prior to answer or within q seconds of answer; andbiasing, by the processor, the probability for the identified call toindicate that a calling party's access network downlink is most likelyto have introduced the poor audio.
 13. The system of claim 9, furthercomprising: identifying, by the processor, a call disconnected between qseconds after answer and r seconds after answer where r is greater thanq; and biasing, by the processor, the probability for the identifiedcall to indicate that the called party's access network uplink is mostlikely to have introduced the poor audio quality.
 14. The computersystem of claim 9, further comprising: identifying, by the processor, acall disconnected between r seconds after answer and s seconds afteranswer, wherein the probability is a function of call talktime.
 15. Thecomputer system of claim 14, further comprising: biasing, by theprocessor, the probability for a call having talktime equal to r toindicate that the calling party's access network uplink or the calledparty's access network downlink is most likely to have introduced thepoor audio quality.
 16. The computer system of claim 14, furthercomprising: biasing, by the processor, the probability to indicate thatthe likelihood that the poor audio quality has been introduced by thecalling party's access network uplink or the called party's accessnetwork downlink decreases as talktime increases.
 17. A computer programproduct, comprising a computer readable hardware storage device storinga computer readable program code, the computer readable program codecomprising an algorithm that when executed by a computer processor of acomputing system implements a method for determining a probability thata particular network segment in a telephony network is responsible forpoor audio quality associated with a telephone call being transmittedover the telephony network, the method comprising: identifying, by aprocessor of a computing system, a plurality of parameters associatedwith a telephone call, wherein the plurality of parameters areindicative of audio quality; and calculating, by a processor, aprobability that a particular network segment is responsible for pooraudio quality associated with the telephone call based on the pluralityof parameters, wherein the probability that a particular network segmentis responsible for the poor audio quality associated with the telephonecall is a function of at least one of: i) a duration of the call, andii) a call disconnect time relative to a call answer time.
 18. Thecomputer program product of claim 17, wherein identifying the pluralityof parameters comprises analyzing at least one voice call recordassociated with the call.
 19. The computer program product of claim 17,further comprising: classifying, by the processor, a call according towhich network segment is likely to be responsible for the poor audioquality associated with the telephone call.
 20. The computer programproduct of claim 17, further comprising: identifying, by the processor,a call lasting less than p seconds which was disconnected prior toanswer or within q seconds of answer; and biasing, by the processor, theprobability for the identified call to indicate that a calling party'saccess network downlink is most likely to have introduced the pooraudio.